Lanhu Context
Converts Lanhu design URLs into AI-ready implementation context including HTML+CSS (Tailwind), image downloads, design tokens, and guidance.
What is Lanhu Context?
Lanhu Context is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to converts lanhu design urls into ai-ready implementation context including html+css (tailwind), image downloads, design tokens, and guidance.
Converts Lanhu design URLs into AI-ready implementation context including HTML+CSS (Tailwind), image downloads, design tokens, and guidance.
This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Converts Lanhu design URLs into AI-ready implementation cont
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx lanhu-contextConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Lanhu Context
What is Lanhu Context?
Lanhu Context is a Model Context Protocol (MCP) server that converts lanhu design urls into ai-ready implementation context including html+css (tailwind), image downloads, design tokens, and guidance. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Lanhu Context?
Follow the installation instructions on the Lanhu Context GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Lanhu Context?
Lanhu Context works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Lanhu Context free to use?
Yes, Lanhu Context is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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Set Up Lanhu Context in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use Lanhu Context?
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